649: Introduction to Machine Learning
Super Data Science: ML & AI Podcast with Jon Krohn
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Supervised and Unsupervised Learning in Machine Learning
The chapter explores the difference between supervised and unsupervised learning in machine learning, highlighting how supervised learning involves known dependent variables with labels while unsupervised learning lacks a dependent variable. It discusses examples like fraud detection in credit card transactions and customer segmentation in malls. The chapter also covers concepts such as regression, classification, false positives, false negatives, true positives, true negatives, and the importance of accuracy ratios in machine learning models.
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